Search Results (10,642)

Freeze–thaw cycles (FTCs) are a prevalent weathering process that threatens the stability of canal slopes in seasonally frozen regions. This study combines direct shear tests under multiple F-T cycles with coupled thermo-hydro-mechanical numerical modeling to investigate the failure mechanisms of slopes with different moisture contents (18%, 22%, 26%). The test results quantify a marked strength degradation, where the cohesion decreases to approximately 50% of its initial value and the internal friction angle is weakened by about 10% after 10 freeze–thaw cycles. The simulation reveals that temperature gradient-driven moisture migration is the core process, leading to a dynamic stress–strain concentration zone that propagates from the upper slope to the toe. The safety factors of the three soil specimens with different moisture contents fell below the critical threshold of 1.3. They registered values of 1.02, 0.99, and 0.78 within 44, 44, and 46 days, which subsequently induced shallow failure. The failure mechanism elucidated in this study enhances the understanding of freeze–thaw-induced slope instability in seasonally frozen regions. Full article

Silica nanoparticles (SNPs) are pivotal in designing functional optical films, but accurately modeling their properties is hindered by the limitations of classical effective medium theories, which break down for larger particles and complex morphologies. We introduce a robust, effective medium theory that overcomes these limitations by incorporating full Mie scattering solutions, thereby accounting for size-dependent and multipolar effects. Our model is comprehensively developed for unshelled, shelled, mixed, and hollow SNPs randomly dispersed in a host medium. Its accuracy is rigorously benchmarked against 3D finite-element method simulations. This work establishes a practical and reliable framework for predicting the optical response of SNP composites, significantly facilitating the rational design of high-performance coatings, such as anti-glare layers, with minimal computational cost. Full article

Organic pollution poses a serious threat to global water safety, while traditional treatment technologies suffer from low efficiency, high costs, and secondary pollution issues. This study successfully develops a highly efficient separation and photocatalytic degradation composite bismuth oxychloride@graphene oxide/polyimide (BiOCl@GO/PI) membrane by loading GO and BiOCl photocatalysts onto PI supporting membrane. The results show that this composite membrane achieves a rejection of 99.8% for methylene blue (MB) and 87.6% for tetracycline hydrochloride (TC). Under UV irradiation, the membrane exhibits a retention rate decline of only 6.8% after five cycles, with water flux stably maintaining at 605 L m⁻² h⁻¹ bar⁻¹. Compared to dark conditions, it demonstrates remarkable flux recovery. This is attributed to the membrane’s excellent photocatalytic degradation activity under UV irradiation. After five degradation cycles, the degradation efficiency is decreased from 97.5 to 88.3%. Studies on radical scavengers indicate that UV irradiation generates free radicals, thereby conferring excellent catalytic activity to the membrane. Its unique synergistic effect between separation and photocatalysis endows it with outstanding self-cleaning performance. This research provides an innovative integrated solution for antibiotic pollution control, demonstrating significant potential for environmental applications. Full article

Litchi (Litchi chinensis Sonn.) is a pillar of the tropical agricultural economy in southern China, yet its production faces increasing instability due to climate change. Traditional agronomic models often fail to capture the complex, non-linear interactions between meteorological drivers and yield formation in perennial fruit trees. To address this challenge, the study constructed a yield prediction framework using an optimized Random Forest (RF) model integrated with interpretable machine learning (SHAP), based on a comprehensive dataset from 17 major production regions in Hainan Province (2000–2022). The model demonstrated robust predictive capability at the provincial scale (R² = 0.564, RMSE = 2.1 t/ha) and high consistency across regions (R² ranging from 0.51 to 0.94). Feature importance analysis revealed that heat accumulation (specifically growing degree days above 20 °C) is the dominant driver, explaining over 85% of yield variability. Crucially, scenario simulations uncovered asymmetric climate risks across phenological stages: while moderate warming generally enhances yield by promoting vegetative growth and ripening, it acts as a stressor during the Fruit Development stage, where temperatures exceeding 26 °C trigger yield decline. Furthermore, the yield penalty for drought during Flowering (−8.09%) far outweighed the marginal benefits of surplus rainfall, identifying this window as critically sensitive to water deficits. These findings underscore the necessity of phenology-aligned adaptation strategies—specifically, securing irrigation during flowering and deploying cooling interventions during fruit development—providing a data-driven basis for climate-smart management in tropical agriculture. Full article

Tropical cyclones typically weaken rapidly during poleward propagation due to decreasing sea surface temperatures and increasing vertical wind shear. Super Typhoon Oscar (1995) deviated from this pattern by maintaining Category-5 intensity at an anomalously high latitude. This study investigates the oceanic mechanisms driving this resilience by integrating satellite SST data with atmospheric (ERA5) and oceanic (HYCOM) reanalysis products. Our analysis shows that the storm track intersected a persistent marine heatwave (MHW) characterized by a deep thermal anomaly extending to approximately 150 m. This elevated heat content formed a strong stratification barrier at the base of the mixed layer (~32 m) that prevented the typical entrainment of cold thermocline water. Instead, storm-induced turbulence mixed warm subsurface water upward to effectively mitigate the negative cold-wake feedback. This process sustained extreme upward enthalpy fluxes exceeding 210 W m⁻² and generated a regime of thermodynamic compensation that enabled the storm to maintain its structure despite an unfavorable atmospheric environment with moderate-to-strong vertical wind shear (15–20 m s⁻¹). These results indicate that the three-dimensional ocean structure acts as a more reliable predictor of typhoon intensity than SST alone in regions affected by MHWs. As MHWs deepen under climate warming, this cold-wake mitigation mechanism is likely to become a significant factor influencing future high-latitude cyclone hazards. Full article

Silicon oxide/graphite (SiO_x/Gr) anodes are promising candidates for high energy-density lithium-ion batteries. However, their complex multiphysics degradation mechanisms pose challenges for accurately interpreting and predicting capacity fade behavior. In particular, existing multiphysics models typically treat gas generation and solid electrolyte interphase (SEI) growth as independent or unidirectionally coupled processes, neglecting their bidirectional interactions. Here, we develop an electro–thermal–mechanical–gaseous coupled model to capture the dominant degradation processes in SiO_x/Gr anodes, including SEI growth, gas generation, SEI formation on cracks, and particle fracture. Model validation shows that the proposed framework can accurately reproduce voltage responses under various currents and temperatures, as well as capacity fade under different thermal and mechanical conditions. Based on this validated model, a mechanistic analysis reveals two key findings: (1) Gas generation and SEI growth are bidirectionally coupled. SEI growth induces gas release, while accumulated gas in turn regulates subsequent SEI evolution by promoting SEI formation through hindered mass transfer and suppressing it through reduced active surface area. (2) Crack propagation within particles is jointly governed by the magnitude and duration of stress. High-rate discharges produce large but transient stresses that restrict crack growth, while prolonged stresses at low rates promote crack propagation and more severe structural degradation. This study provides new insights into the coupled degradation mechanisms of SiO_x/Gr anodes, offering guidance for performance optimization and structural design to extend battery cycle life. Full article

Greenhouse pesticide application often suffers from low droplet deposition uniformity and health risks to operators. A self-propelled overhead rail air-assisted sprayer has been designed. The mathematical model based on droplet movement and the DPM are used to analyze the equipment’s working principle. Deposition surfaces at 0.4, 0.5, 0.6, and 0.7 m were used to examine the effects of travel speed, external airflow, and spray angle on droplet deposition uniformity. Through one-way analysis of variance, all variables reached a significant level (p < 0.001). Simulation results identified the optimal operating parameters: travel speed of 0.3 m/s, external air-flow velocity of 0.3 m/s, and spray angle of 5°, resulting in droplet deposition densities of 719, 586, 700, and 839 droplets/cm², with a coefficient of variation of 14.57%. The sediment variation coefficients of both the on-site test results and the simulation results were within 10%, which proved the reliability of the numerical simulation. In conclusion, the device proposed in this study effectively enables targeted fog spraying for multi-layer crops in greenhouses, significantly improving pesticide utilization, reducing application costs, and minimizing environmental pollution. It offers reliable technical support for greenhouse pest control operations. Full article

Aged skeletal muscle satellite cells (MuSCs) exhibit impaired autophagy-related activity, reduced proliferative capacity, and compromised myogenic differentiation, which collectively contribute to defective muscle regeneration during aging. However, whether hypoxia-driven modulation of autophagy-related activity can improve aged MuSC function and the underlying molecular mechanisms remain incompletely understood. In this study, aged MuSCs were divided into three groups: normoxia, hypoxia, and hypoxia combined with an autophagy inhibitor. Aged MuSCs exhibited a decreased LC3B-II/LC3B-I ratio and Beclin-1 expression, together with elevated p62 levels, indicating altered autophagy-related activity. Hypoxic culture was associated with enhanced autophagy-related activity in aged MuSCs, accompanied by HIF-1α stabilization, BNIP3 upregulation, and reduced p62 accumulation. Functionally, hypoxia significantly promoted the proliferation and myogenic differentiation of aged MuSCs. Pharmacological inhibition of autophagy using 3-methyladenine, as well as BNIP3 suppression, markedly attenuated these hypoxia-induced functional improvements. Collectively, these findings suggest that hypoxia is associated with improved proliferative and myogenic capacities of aged MuSCs, potentially involving autophagy-related activity regulated by the HIF-1α/BNIP3 pathway. This study provides insight into the relationship between hypoxic signaling and autophagy in aged MuSCs and may inform future strategies aimed at improving muscle regeneration during aging. Full article

Ganoderma lucidum triterpenoids (GLTs) exhibit potential anti-obesity activity. However, their mechanism remains unclear. In this study, triterpenoids were extracted from G. lucidum via ultrahigh-pressure extraction. Using a high-fat diet (HFD)-induced mouse model, we showed that GLT treatment (100 and 200 mg/kg) significantly reduced body weight and lipid accumulation without changing food intake. Next, we found that GLT significantly inhibited preadipocyte differentiation and adipogenesis and reduced the expression of adipogenic genes, including PPARγ, C/EBPα, FASN, and SCD-1. Moreover, network pharmacology predicted a total of 306 potential targets, among which FYN, PRKCQ, PTPRF, HRH1, and HCRTR2 were identified as the core targets via a machine learning algorithm. Interestingly, GLT upregulated the expression of PRKCQ, while the deletion of PRKCQ significantly reversed the anti-adipogenic effect of GLT. In addition, we found that neutral GLT may play a dominant role in inhibiting adipogenic differentiation. These findings suggest for the first time that GLT inhibits adipogenesis and lipid accumulation via the induction of PRKCQ in adipocytes. This study provides a scientific basis for the application of GLT in the prevention and treatment of obesity, as both a pharmaceutical agent and a functional food. Full article

Acoustic-based anomaly detection in elevators is crucial for predictive maintenance and operational safety, yet it faces significant challenges in real-world settings, including pervasive multi-source acoustic interference within confined spaces and severe class imbalance in collected data, which critically degrades the detection performance for minority yet critical acoustic events. To address these issues, this study proposes a novel hierarchical self-distillation framework. The method embeds auxiliary classifiers into the intermediate layers of a backbone network, creating a deep teacher–shallow student knowledge transfer paradigm optimized jointly via Kullback–Leibler divergence and feature alignment losses. A self-attentive temporal pooling layer is introduced to adaptively weigh discriminative time-frequency features, thereby mitigating temporal overlap interference, while a focal loss function is employed specifically in the teacher model to recalibrate the learning focus towards hard-to-classify minority samples. Extensive evaluations on the public UrbanSound8K dataset and a proprietary industrial elevator audio dataset demonstrate that the proposed model achieves superior performance, exceeding 90% in both accuracy and F1-score. Notably, it yields substantial improvements in recognizing rare events, validating its robustness for elevator acoustic monitoring. Full article

High-precision short-term photovoltaic (PV) power prediction has become a critical technology in ensuring grid accommodation capacity, optimizing dispatching decisions, and enhancing plant economic benefits. This paper proposes a long short-term memory (LSTM)-based short-term PV power prediction method with the genetic algorithm (GA)-optimized adaptive fusion of space-based cloud imagery and ground-based meteorological data. The effective integration of satellite cloud imagery is conducted in the PV power prediction system, and the proposed method addresses the issues of low accuracy, poor robustness, and inadequate adaptation to complex weather associated with using a single type of meteorological data for PV power prediction. The multi-source heterogeneous data are preprocessed through outlier detection and missing value imputation. Spearman correlation analysis is employed to identify meteorological attributes highly correlated with PV power output. A dedicated dataset compatible with LSTM algorithm-based prediction models is constructed. An LSTM prediction model with a GA algorithm-based adaptive multi-source heterogeneous data fusion method is proposed, and the ability to construct a precise short-term PV power prediction model is demonstrated. Experimental results demonstrate that the proposed method outperforms single-source LSTM, single-source CNN-LSTM, and dual-source CNN-Transformer models in prediction accuracy, achieving an RMSE of 0.807 kWh and an MAPE of 6.74% on a critical test day. The proposed method enables real-time precision forecasting for grid dispatch centers and lightweight edge deployment at PV plants, enhancing renewable energy integration while effectively mitigating grid instability from power fluctuations. Full article

Effective recognition of potential threats is crucial for survival in aquatic habitats, especially for amphibian larvae. As a critically endangered species, understanding how the Chinhai spiny newt (Echinotriton chinhaiensis) larvae recognize novel predators provides key scientific support for developing targeted conservation strategies. Using the American bullfrog (Lithobates catesbeiana) as a representative predator, we examined larval responses by presenting isolated visual or chemical cues, as well as visual cues from predators of differing body sizes. We measured larval avoidance and activity. Results showed that with only visual cues, larvae quickly avoided the bullfrog and significantly reduced their activity compared to controls. With only chemical cues, activity decreased significantly, but avoidance behavior did not. When both large and small bullfrogs were present, larvae avoided the larger individual significantly more. These findings demonstrate that E. chinhaiensis larvae can use visual or chemical cues to detect novel potential predators and assess risk based on size to guide their avoidance behavior. This study provides key empirical data for understanding anti-predator responses in endangered caudate amphibians and informs conservation strategies against potential threats. Full article

Vascular endothelial injury is a key pathological characteristic of multiple diseases, such as atherosclerosis, stroke, and mastitis. Aspirin eugenol ester (AEE) has been confirmed to exert a significant protective effect on vascular endothelial injury. However, the universal action patterns and underlying mechanisms of AEE across different pathological scenarios have not been systematically elucidated. This study aimed to investigate the effect and mechanism of AEE in alleviating multiple vascular endothelial injury models. Nine vascular endothelial injury models were established by treating bovine aortic endothelial cells (BAECs), mouse aortic endothelial cells (MAECs), and human umbilical vein endothelial cells (Huvecs) with ethanol (EtOH), hydrogen peroxide (H₂O₂), and copper sulfate (CuSO₄), respectively. The protective effects of AEE were systematically evaluated via morphological observation, detection of inflammatory responses, and oxidative stress markers. Furthermore, metabolomics was employed to identify and analyze differentially expressed metabolites between the nine model groups and AEE groups. AEE exerted protective effects on all nine vascular endothelial injury models, inhibiting inflammation and oxidative stress induced by all inducers. Metabolomic analysis revealed that the differentially expressed metabolites modulated by AEE in most models were primarily enriched in lipid metabolism, amino acid metabolism, coenzyme biosynthesis, and other related pathways. AEE could improve vascular endothelial injury by upregulating antioxidant substance which included eicosapentaenoic acid (EPA), choline, coenzyme A (CoA), glutathione (GSH), catalase (CAT) and superoxide dismutase (SOD), as well as downregulating substances that cause endothelial oxidative damage, including phytosphingosine (PS), palmitic acid (PA), and arachidonic acid (AA). Full article